SoroushVahidi/scidocs huggingface dataset:
Multi-layer FSS for gain improvement of a wide-band stacked printed antenna
(2015)

In this paper, an attempt has been made to improve the gain of a wide-band antenna using two layers of frequency-selective surfaces. It is seen that using two layers it is possible to achieve flat transmission characteristics over a reasonable bandwidth. However with an actual antenna, the gain improvement has at present been achieved over only a small band. It is expected that with further optimization and possibly increasing the number of layers, wide-band gain enhancement can be achieved.
Power-Management Architecture of the Intel Microarchitecture Code-Named Sandy Bridge
(2012)

Modern microprocessors are evolving into system-on-a-chip designs with high integration levels, catering to ever-shrinking form factors. Portability without compromising performance is a driving market need. An architectural approach that's adaptive to and cognizant of workload behavior and platform physical constraints is indispensable to meeting these performance and efficiency goals. This article describes power-management innovations introduced on Intel's Sandy Bridge microprocessor.
All-printed diode operating at 1.6 GHz.
(2014)

Printed electronics are considered for wireless electronic tags and sensors within the future Internet-of-things (IoT) concept. As a consequence of the low charge carrier mobility of present printable organic and inorganic semiconductors, the operational frequency of printed rectifiers is not high enough to enable direct communication and powering between mobile phones and printed e-tags. Here, we report an all-printed diode operating up to 1.6 GHz. The device, based on two stacked layers of Si and NbSi2 particles, is manufactured on a flexible substrate at low temperature and in ambient atmosphere. The high charge carrier mobility of the Si microparticles allows device operation to occur in the charge injection-limited regime. The asymmetry of the oxide layers in the resulting device stack leads to rectification of tunneling current. Printed diodes were combined with antennas and electrochromic displays to form an all-printed e-tag. The harvested signal from a Global System for Mobile Communications mobile phone was used to update the display. Our findings demonstrate a new communication pathway for printed electronics within IoT applications.
AllConcur: Leaderless Concurrent Atomic Broadcast (Extended Version)
(2016)

Many distributed systems require coordination between the components involved. With the steady growth of such systems, the probability of failures increases, which necessitates scalable fault-tolerant agreement protocols. The most common practical agreement protocol, for such scenarios, is leader-based atomic broadcast. In this work, we propose ALLCONCUR, a distributed system that provides agreement through a leaderless concurrent atomic broadcast algorithm, thus, not suffering from the bottleneck of a central coordinator. In ALLCONCUR, all components exchange messages concurrently through a logical overlay network that employs early termination to minimize the agreement latency. Our implementation of ALLCONCUR supports standard sockets-based TCP as well as high-performance InfiniBand Verbs communications. ALLCONCUR can handle up to 135 million requests per second and achieves 17× higher throughput than today’s standard leader-based protocols, such as Libpaxos. Thus, ALLCONCUR is highly competitive with regard to existing solutions and, due to its decentralized approach, enables hitherto unattainable system designs in a variety of fields.
Short-Term Power Load Forecasting with Deep Belief Network and Copula Models
(2017)

The complexity and uncertainty in scheduling and operation of the power system are prominently increasing with the penetration of smart grid. An essential task for the effective operation of power systems is the power load forecasting. In this paper, a tandem data-driven method is studied in this research based on deep learning. A deep belief network (DBN) embedded with parametric Copula models is proposed to forecast the hourly load of a power grid. Data collected over a whole year from an urbanized area in Texas, United States is utilized. Forecasting hourly power load in four different seasons in a selected year is examined. Two forecasting scenarios, day-ahead and week-ahead forecasting are conducted using the proposed methods and compared with classical neural networks (NN), support vector regression machine (SVR), extreme learning machine (ELM), and classical deep belief networks (DBN). The accuracy of the forecasted power load is assessed by mean absolute percentage error (MAPE) and root mean square error (RMSE). Computational results confirm the effectiveness of the proposed semi-parametric data-driven method.
Text Classification with Topic-based Word Embedding and Convolutional Neural Networks
(2016)

Recently, distributed word embeddings trained by neural language models are commonly used for text classification with Convolutional Neural Networks (CNNs). In this paper, we propose a novel neural language model, Topic-based Skip-gram, to learn topic-based word embeddings for biomedical literature indexing with CNNs. Topic-based Skip-gram leverages textual content with topic models, e.g., Latent Dirichlet Allocation (LDA), to capture precise topic-based word relationship and then integrate it into distributed word embedding learning. We then describe two multimodal CNN architectures, which are able to employ different kinds of word embeddings at the same time for text classification. Through extensive experiments conducted on several real-world datasets, we demonstrate that combination of our Topic-based Skip-gram and multimodal CNN architectures outperforms state-of-the-art methods in biomedical literature indexing, clinical note annotation and general textual benchmark dataset classification.
EROS: a fast capability system
(1999)

EROS is a capability-based operating system for commodity processors which uses a single level storage model. The single level store's persistence is transparent to applications. The performance consequences of support for transparent persistence and capability-based architectures are generally believed to be negative. Surprisingly, the basic operations of EROS (such as IPC) are generally comparable in cost to similar operations in conventional systems. This is demonstrated with a set of microbenchmark measurements of semantically similar operations in Linux.The EROS system achieves its performance by coupling well-chosen abstract objects with caching techniques for those objects. The objects (processes, nodes, and pages) are well-supported by conventional hardware, reducing the overhead of capabilities. Software-managed caching techniques for these objects reduce the cost of persistence. The resulting performance suggests that composing protected subsystems may be less costly than commonly believed.
Simple Method for High-Performance Digit Recognition Based on Sparse Coding
(2008)

In this brief paper, we propose a method of feature extraction for digit recognition that is inspired by vision research: a sparse-coding strategy and a local maximum operation. We show that our method, despite its simplicity, yields state-of-the-art classification results on a highly competitive digit-recognition benchmark. We first employ the unsupervised Sparsenet algorithm to learn a basis for representing patches of handwritten digit images. We then use this basis to extract local coefficients. In a second step, we apply a local maximum operation to implement local shift invariance. Finally, we train a support vector machine (SVM) on the resulting feature vectors and obtain state-of-the-art classification performance in the digit recognition task defined by the MNIST benchmark. We compare the different classification performances obtained with sparse coding, Gabor wavelets, and principal component analysis (PCA). We conclude that the learning of a sparse representation of local image patches combined with a local maximum operation for feature extraction can significantly improve recognition performance.
Standard cell library and automated design flow for circuits on flexible substrates
(2009)

A-Si:H TFTs are traditionally used in backplane arrays for active matrix displays and occasionally in row or column drive electronics with current efforts focusing on flexible displays and drivers. This paper extends flexible electronics to complex digital circuitry by designing a standard cell library for a-Si:H TFTs on flexible stainless steel and plastic substrates. The standard cell library enables layout automation with a standard cell place and route tool, significantly speeding the layout of a-Si:H digital circuits on the backplane to enhance display functionality. Since only n-channel transistors are available, the gates are designed with a bootstrap pull-up network to ensure good output voltage swings. The library developed consists of 7 gates: 5 combinational gates (Inverter, NAND2, NOR2, NOR3, and MUX2) and 2 sequential gates (latch and ‘D’ flip-flop). Test structures have been fabricated to experimentally characterize the delay vs. fan-out of the standard cells. Automatic extraction of electrical interconnections from layout, enabling layout versus schematic (LVS) has also incorporated into the existing tool suite for bottom gate a-Si:H TFTs. A 3bit counter was designed, fabricated and tested to demonstrate the standard cell library is described.
Challenges Facing the Industrial Implementation of Fog Computing
(2018)

Recently, the industries converge to the integration of the industry 4.0 paradigm to keep responding to the variable market demands. This integration is realized by the adoption of several components of the industry 4.0 such as IoT, Big Data and Cloud Computing, etc. Several difficulties concerning the integration of data management were encountered during first level of Industry 4.0 integration because of the unexpected quantity of data generated by IoT devices. The Fog computing can be considered as a new component of Industry 4.0 to resolve this kind of problem. However its implementation in the industrial field faces several challenges from different natures. This paper explains the role of Fog Computing solution to enhance the Cloud layer (distribution, low latency, real-time,. . . ) and studies its ability to be implemented in manufacturing systems. The Fog Manufacturing is introduced as the new industrial Fog vision. The challenges preventing the Fog Manufacturing implementation are studied and the links between each other are justified. A future use case is described to carry out the solutions given to satisfy the Fog Manufacturing challenges.
An empirical study of dormant bugs
(2014)

Over the past decade, several research efforts have studied the quality of software systems by looking at post-release bugs. However, these studies do not account for bugs that remain dormant (i.e., introduced in a version of the software system, but are not found until much later) for years and across many versions. Such dormant bugs skew our under- standing of the software quality. In this paper we study dormant bugs against non-dormant bugs using data from 20 different open-source Apache foundation software systems. We find that 33% of the bugs introduced in a version are not reported till much later (i.e., they are reported in future versions as dormant bugs). Moreover, we find that 18.9% of the reported bugs in a version are not even introduced in that version (i.e., they are dormant bugs from prior versions). In short, the use of reported bugs to judge the quality of a specific version might be misleading. Exploring the fix process for dormant bugs, we find that they are fixed faster (median fix time of 5 days) than non- dormant bugs (median fix time of 8 days), and are fixed by more experienced developers (median commit counts of developers who fix dormant bug is 169% higher). Our results highlight that dormant bugs are different from non-dormant bugs in many perspectives and that future research in software quality should carefully study and consider dormant bugs.
Chronic ulcerative stomatitis: a distinct clinical entity?
(2011)

Chronic ulcerative stomatitis (CUS) is a mucocutaneous disorder which is characterised by persistent oral mucosal ulceration. The clinical appearance is often reminiscent of oral lichen planus (OLP) leading to erroneous diagnoses. The immune mediated inhibition of the CUS protein (CUSP) is implicated in the pathogenesis of CUS. CUSP acts as an anti-apoptotic protein and when its action is prevented it may result in significant epithelial injury. The objective or this article is to present the first documented case of CUS in South Africa, with relevant reference to current international literature. CUS should be considered in patients previously diagnosed with OLP but who are unresponsive to glucocorticosteroid therapy. The condition can be successfully managed using hydroxychloroquine.
Small and fast moving object detection and tracking in sports video sequences
(2004)

We propose an algorithm for detection and tracking of small and fast moving objects, like a ping pong ball or a cricket ball, in sports video sequences. For detection, the proposed method uses only motion as a cue; moreover it does not use any texture information. Our method is able to detect the object with very low contrast and negligible texture content. Along with detection, we also propose a tracking algorithm using the multiple filter bank approach. Thus we provide a complete solution. The tracking algorithm is able to track maneuvering as well as non-maneuvering movements of the object without using any a priori information about the target dynamics
Social entrepreneurship research : A source of explanation , prediction , and delight
(2006)

Social entrepreneurship, as a practice and a field for scholarly investigation, provides a unique opportunity to challenge, question, and rethink concepts and assumptions from different fields of management and business research. This article puts forward a view of social entrepreneurship as a process that catalyzes social change and addresses important social needs in a way that is not dominated by direct financial benefits for the entrepreneurs. Social entrepreneurship is seen as differing from other forms of entrepreneurship in the relatively higher priority given to promoting social value and development versus capturing economic value. To stimulate future research the authors introduce the concept of embeddedness as a nexus between theoretical perspectives for the study of social entrepreneurship. # 2005 Elsevier Inc. All rights reserved.
Ultrasound measurements of axillary recess capsule thickness in unilateral frozen shoulder: study of correlation with MRI measurements
(2018)

The aims of this study were to compare the ultrasound thickness of the affected axillary recess capsule (ARC) with that of the unaffected ARC in patients with frozen shoulder (FS), to analyze whether the ultrasound measurements of the ARC thickness correlate with those obtained using MRI, and to assess whether the ultrasound thickness of the ARC correlates with the patterns of range of motion limitation. Forty-four patients with clinically diagnosed unilateral FS and MRI evaluation performed ultrasound measurement of ARC. The ultrasound measurement of the ARC thickness was performed with the patients in a supine position with their shoulder abducted by 40°. The ARC thickness was also measured by MRI on oblique coronal images by another physician blinded to the ultrasound measurements. With both ultrasound and MRI, ARC thickness was determined at the widest portion of the capsule. The ultrasound thickness of ARC was significantly higher in the affected shoulder (4.4 ± 1.1 mm) than in the unaffected one (2.2 ± 0.5 mm) (p < 0.001). The ultrasound thickness of the ARC in the affected shoulder correlated with that measured by MRI (8.9 ± 1.9 mm) (p < 0.001, r = 0.83). The ARC thickness, whether measured by ultrasound or MRI, was not significantly related to the limitation of movement in specific directions. Ultrasound can demonstrate the difference in ARC thickness between affected and unaffected shoulders in patients with unilateral FS. The ARC thickness measured by ultrasound correlates with that measured by MRI.
A scaling normalization method for differential expression analysis of RNA-seq data
(2009)

The fine detail provided by sequencing-based transcriptome surveys suggests that RNA-seq is likely to become the platform of choice for interrogating steady state RNA. In order to discover biologically important changes in expression, we show that normalization continues to be an essential step in the analysis. We outline a simple and effective method for performing normalization and show dramatically improved results for inferring differential expression in simulated and publicly available data sets.
Detecting People in Artwork with CNNs
(2016)

CNNs have massively improved performance in object detection in photographs. However research into object detection in artwork remains limited. We show state-of-the-art performance on a challenging dataset, People-Art, which contains people from photos, cartoons and 41 different artwork movements. We achieve this high performance by fine-tuning a CNN for this task, thus also demonstrating that training CNNs on photos results in overfitting for photos: only the first three or four layers transfer from photos to artwork. Although the CNN’s performance is the highest yet, it remains less than 60% AP, suggesting further work is needed for the cross-depiction problem.
Introduction to Space-Time Wireless Communications
(2003)

published by the press syndicate of the university of cambridge A catalog record for this book is available from the British Library ISBN 0 521 82615 2 hardback Contents List of figures page xiv List of tables xxii Preface xxiii List of abbreviations xxvi List of symbols xxix vii viii Contents 2.6 Polarization and field diverse channels 27 2.7 Antenna array topology 28 2.8 Degenerate channels 29 2.9 Reciprocity and its implications 31 3 ST channel and signal models
A quasi-orthogonal space-time block code
(2000)

It has been shown that a complex orthogonal design that provides full diversity and full transmission rate for a space–time block code is not possible for more than two antennas. Previous attempts have been concentrated in generalizing orthogonal designs which provide space–time block codes with full diversity and a high transmission rate. In this work, we design rate one codes which are quasi-orthogonal and provide partial diversity. The decoder of the proposed codes works with pairs of transmitted symbols instead of single symbols.
Space-Time block codes from orthogonal designs
(1999)

We introduce space–time block coding , a new paradigm for communication over Rayleigh fading channels using multiple transmit antennas. Data is encoded using a space–time block code and the encoded data is split inton streams which are simultaneously transmitted usingn transmit antennas. The received signal at each receive antenna is a linear superposition of the n transmitted signals perturbed by noise. Maximumlikelihood decoding is achieved in a simple way through decoupling of the signals transmitted from different antennas rather than joint detection. This uses the orthogonal structure of the space–time block code and gives a maximum-likelihood decoding algorithm which is based only on linear processing at the receiver. Space–time block codes are designed to achieve the maximum diversity order for a given number of transmit and receive antennas subject to the constraint of having a simple decoding algorithm. The classical mathematical framework of orthogonal designs is applied to construct space–time block codes. It is shown that space–time block codes constructed in this way only exist for few sporadic values ofn. Subsequently, a generalization of orthogonal designs is shown to provide space–time block codes for both real and complex constellations for any number of transmit antennas. These codes achieve the maximum possible transmission rate for any number of transmit antennas using any arbitrary real constellation such as PAM. For an arbitrary complex constellation such as PSK and QAM, space–time block codes are designed that achieve1=2 of the maximum possible transmission rate for any number of transmit antennas. For the specific cases of two, three, and four transmit antennas, space–time block codes are designed that achieve, respectively, all, 3=4, and 3=4 of maximum possible transmission rate using arbitrary complex constellations. The best tradeoff between the decoding delay and the number of transmit antennas is also computed and it is shown that many of the codes presented here are optimal in this sense as well.
Space-Time Codes for High Data Rate Wireless Communications
(2002)

Space-time codes (STC) are a class of signaling techniques, offering coding and diversity gains along with improved spectral efficiency. These codes exploit both the spatial and the temporal diversity of the wireless link by combining the design of the error correction code, modulation scheme and array processing. STC are well suited for improving the downlink performance, which is the bottleneck in asymmetric applications such as downstream Internet. Three original contributions to the area of STC are presented in this dissertation. First, the development of analytic tools that determine the fundamental limits on the performance of STC in a variety of channel conditions. For trellis-type STC, transfer function based techniques are applied to derive performance bounds over Rayleigh, Rician and correlated fading environments. For block-type STC, an analytic framework that supports various complex orthogonal designs with arbitrary signal cardinalities and array configurations is developed. In the second part of the dissertation, the Virginia Tech Space-Time Advanced Radio (VT-STAR) is designed, introducing a multi-antenna hardware laboratory test bed, which facilitates characterization of the multiple-input multiple-output (MIMO) channel and validation of various space-time approaches. In the third part of the dissertation, two novel space-time architectures paired with iterative processing principles are proposed. The first scheme extends the suitability of STC to outdoor wireless communications by employing iterative equalization/decoding for time dispersive channels and the second scheme employs iterative interference cancellation/decoding to solve the error propagation problem of Bell-Labs Layered Space-Time Architecture (BLAST). Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding.
Haplogroup Prediction from Y-STR Values Using an Allele-Frequency Approach
(2005)

A new approach to predicting the Y-chromosome haplogroup from a set of Y-STR marker values is presented and compared to other approaches. The method has been implemented in an Excel-based program, where an arbitrary number of STR markers may be input and a “goodness of fit” score for 10 haplogroups (E3a, E3b, G, I1a, I1b, I1c, J2, N3, R1a, and R1b) is returned. This method has been applied to 101 R1b haplotypes and 50 I1a haplotypes (all having 37 STR markers available), and the distribution of results is presented. In the case of I1a, the results are compared with the predictions of another method.
A design of miniaturization LPDA antenna with ultra wideband
(2015)

This paper designed a Log-periodic miniaturization antenna working in 8GHz to 18GHz. It satisfies the characteristic of high gain, good radiation pattern, and a large proportion of the size reduction which other antenna don't possess. The lengthwise is 80mm, it reduces more than 50% of the transverse dimension with the original specification. A “mountain” terminal loaded design is used to shrink size of antenna under the premise of guaranteeing directivity of antenna. By optimizing backward feeding structure and antenna array to improve antenna performance. The final result is superior to other same type antenna distinctly.